Participatory ergonomics: Understanding the contributions of reflection groups in a hospital food service

Aim: To identify how the methodology of Reflection Groups (RG) can contribute to approach social-psychological problems, so often observed as obstacles in PE efforts. The objective was also to verify the contributions from RG to the implementation of ergonomics recommendations, which were a starting point and organized group discussions. Method: A concrete case was used as an illustration, and studied in depth: RG with administration and production workers` representatives from the Department of Nutrition and Dietetics of a cardiologic hospital in Sao Paulo, Brazil. RG are temporary thinking groups, taking place outside the workplace and having delegative and consultive participation. They make use of Operative Groups, an adapted form of tripartite group, activity as an instrumental resource, group dynamic techniques and videotaping. In 2007, 31 meetings took place during paid working hours with 7 groups of different composition, ranging from 1.5 h to 3 h. Results: Additionally to the positive effects in communication and psychosocial environment, RG could also contribute to changes in interpersonal relationships, cooperation, personal and work behaviours. By dealing with aspects which could hinder the explicit task: fears, conflicts, and stereotyped beliefs and behaviours; resistance to change could be broken and group members could learn. RG allowed input about new risks; continuous information and feedback about ongoing ergonomics interventions so that immediate corrective action could be taken. The main form of participation was in administrative, organizational, and psychosocial problems which required a better clarification and identification of their real causes, commitment, and elaboration of strategies and negotiation of different stakeholders in their solution. Conclusion: RG takes advantage of homogeneous and heterogeneous groups, in face to face communication. The interactions in the groups are task-oriented (explicit task) but attaining groups` goals depends on a relational interaction (implicit task). Relevance to industry: Reflection groups can bring important contributions to ergonomics and industry because they favour the discussion, disclosure of problems and incorporation of solutions, enabling interventions in working organization, psychosocial environment and relationships in a collective and participatory approach, promoting health and social integration. (C) 2010 Elsevier B.V. All rights reserved.

Service guarantees: A strategic mechanism to minimise customers' perceived risk in service organisations

Service offerings are largely intangible in nature. Customers are thus unable to assess the purchase outcome prior to experience, rendering the risk of possible customer dissatisfaction very high. It is argued that the concept of service guarantees proposed by services management theory can be effectively utilised to reduce the perceived risk of dissatisfaction for the customer in service organisations. Additionally, it is suggested that service guarantees force management to undertake activities which elevate the superiority of the organisation in the eyes of the customer and, thus, the opportunity to transform one-time customers into loyal ones. The purpose of this paper is twofold: first, to illustrate how customers’ behavioural intentions can be influenced by the use of a service guarantee; and second, to outline a systematic process that can help service business managers to develop and implement an effective service guarantee. This research highlights the numerous benefits available to service organisations by utilising the service guarantee as a strategic tool. Some of the important management implications are also outlined.

Reliability factors in business software: volatility, requirements and end-users

Many business-oriented software applications are subject to frequent changes in requirements. This paper shows that, ceteris paribus, increases in the volatility of system requirements decrease the reliability of software. Further, systems that exhibit high volatility during the development phase are likely to have lower reliability during their operational phase. In addition to the typically higher volatility of requirements, end-users who specify the requirements of business-oriented systems are usually less technically oriented than people who specify the requirements of compilers, radar tracking systems or medical equipment. Hence, the characteristics of software reliability problems for business-oriented systems are likely to differ significantly from those of more technically oriented systems.

Archetype change in professional organizations: Survey evidence from large law firms

This paper examines the proposition that the traditional archetype of the professional partnership is said to have changed into a more 'business-like' entity, the managed professional business. It broadens the restricted case sample base on which much of the evidence has been adduced, by developing a survey questionnaire through which 197 large British law firms were sampled. Change, consistent with the notion of a more commercially oriented and consciously managed organization, is concentrated in the market-facing area of the firm but coexists with areas of continuity in the governance of the firm and its strategic management. The findings reveal a more managerial form of organization in which the core elements of the traditional form of professional organization have not been transformed. These results contest the assertion of either transformational or sedimented change found in other, case-based research and suggest that archetype change needs theoretically to be distinguished from the general phenomenon of greater managerialism within the professional service firm.

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

E-service em bibliotecas: gera ao de valor para pesquisadores por meio de coopera ao indireta

O conceito de cooperação indireta aplicado a dados de transações de empréstimos do acervo de uma biblioteca pode ser usado para gerar recomendações de itens relevantes para usuários e pesquisadores. O modelo proposto utiliza a Análise de Agrupamentos e a Análise de Cestas e tem aplicabilidade direta em livrarias virtuais, podendo ser adaptado a praticamente qualquer tipo de empreendimento em e-business.

Knowledge cities: a taxonomy for analyzing software and information service clusters

Software and information services (SIS) have become a field of increasing opportunities for international trade due to the worldwide diffusion of a combination of technological and organizational innovations. In several regions, the software industry is organized in clusters, usually referred to as "knowledge cities" because of the growing importance of knowledge-intensive services in their economy. This paper has two primary objectives. First, it raises three major questions related to the attractiveness of different cities in Argentina and Brazil for hosting software companies and to their impact on local development. Second, a new taxonomy is proposed for grouping clusters according to their dominant business segment, ownership pattern and scope of operations. The purpose of this taxonomy is to encourage further studies and provide an exploratory analytical tool for analyzing software clusters.

Web 2.0 and its impact on knowledge and business organizations

Today, information overload and the lack of systems that enable locating employees with the right knowledge or skills are common challenges that large organisations face. This makes knowledge workers to re-invent the wheel and have problems to retrieve information from both internal and external resources. In addition, information is dynamically changing and ownership of data is moving from corporations to the individuals. However, there is a set of web based tools that may cause a major progress in the way people collaborate and share their knowledge. This article aims to analyse the impact of ‘Web 2.0’ on organisational knowledge strategies. A comprehensive literature review was done to present the academic background followed by a review of current ‘Web 2.0’ technologies and assessment of their strengths and weaknesses. As the framework of this study is oriented to business applications, the characteristics of the involved segments and tools were reviewed from an organisational point of view. Moreover, the ‘Enterprise 2.0’ paradigm does not only imply tools but also changes the way people collaborate, the way the work is done (processes) and finally impacts on other technologies. Finally, gaps in the literature in this area are outlined.

Improving management skills through business simulation

A survey was conducted among students of the Accounting and Administration undergraduate degree at ISCAP – IPP (School of Accounting and Administration of Polytechnic Institute of Porto) in order to understand their perception value of their course Business Simulation (BS). This course is provided in a business environment where students can learn by doing through the management of a company as they were in the real life, but risk-free. The learning tasks are provided in an action-oriented format to maximize the learning process. Students learn by doing a set of tasks every session and have also to produce reports and presentations during the course. BS is part of the undergraduate degree of Accounting and Administration at ISCAP – IPP since the beginning of 2003. The questionnaire we used captured the students’ perception about general and specific skills and competencies considered important for managers and accountants in the real life, about the methodology used in the course, which is totally different from the traditional form, and also about the adequacy of the course included as part of the undergraduate degree. The results showed that students’ perception is highly positive and almost all of them think they improve the skills needed for a job during the course. These results are consistent with [1] Adler and Milne’s research in which the authors found that students agree with the use of action-oriented learning tasks in order to provide them the needed attitudes, skills, and knowledge. The improvement of group skills is the most important issue for students, which can be understandable as BS is the only course from the degree in Accounting and Administration they really have to work in groups.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.